Adapting ordered fuzzy numbers to the evaluation of the isolation level of slices

IF 6.8 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Tomasz W. Nowak, Zbigniew Kotulski
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引用次数: 0

Abstract

A fuzzy logic approach is suitable for modeling problems where some elements (mutual and external relations of components, their properties, parameters, etc.) are subject to non-statistical uncertainty. The ordered fuzzy numbers proved an effective tool for quantitatively analyzing such problems. In this paper, we propose applying ordered fuzzy numbers to evaluate the security isolation level of slices in contemporary computer networks, especially 5G networks. Based on the earlier studies, we introduce the idea of the isolation of slices and examples of evaluating the isolation level (experimentally and by numerical calculations). We propose using the ordered fuzzy numbers to describe the parameters of security isolation of the network's components and, then, to estimate the security isolation level of the whole slice. We also propose some practical approaches to evaluating the isolation level and give an illustrative example of how such an approach works in practice.
将有序模糊数应用于切片隔离度的评价
模糊逻辑方法适用于某些元素(组件之间的相互关系和外部关系、属性、参数等)具有非统计不确定性的建模问题。有序模糊数是定量分析这类问题的有效工具。在本文中,我们提出了应用有序模糊数来评估当代计算机网络,特别是5G网络中切片的安全隔离级别。在前人研究的基础上,我们引入了切片隔离的思想,并给出了评估切片隔离水平的实例(实验和数值计算)。我们提出用有序模糊数来描述网络各组成部分的安全隔离参数,进而估计整个切片的安全隔离级别。我们还提出了一些评估隔离级别的实用方法,并给出了一个示例,说明这种方法在实践中是如何工作的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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